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Piecewise linearization of bivariate nonlinear functions: minimizing the number of pieces under a bounded approximation error

Abstract : This work focuses on the approximation of bivariate functions into piecewise linear ones with a minimal number of pieces and under a bounded approximation error. Applications include the approximation of mixed integer nonlinear optimization problems into mixed integer linear ones that are in general easier to solve. A framework to build dedicated linearization algorithms is introduced, and a comparison to the state of the art heuristics shows their efficiency.
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Preprints, Working Papers, ...
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https://hal.laas.fr/hal-03629850
Contributor : Aloïs Duguet Connect in order to contact the contributor
Submitted on : Monday, April 4, 2022 - 3:59:01 PM
Last modification on : Tuesday, October 25, 2022 - 11:58:11 AM
Long-term archiving on: : Tuesday, July 5, 2022 - 6:51:43 PM

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  • HAL Id : hal-03629850, version 1

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Aloïs Duguet, Sandra Ulrich Ngueveu. Piecewise linearization of bivariate nonlinear functions: minimizing the number of pieces under a bounded approximation error. 2022. ⟨hal-03629850v1⟩

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